remove Nadam from automl

autonomio · Apr 21, 2024 · f190198 · f190198
1 parent d5463f3
commit f190198
Show file tree

Hide file tree

Showing 14 changed files with 89 additions and 89 deletions.
diff --git a/docs/Examples_PyTorch.md b/docs/Examples_PyTorch.md
@@ -138,7 +138,7 @@ return net, net.parameters()
 
 ```python
 p = {'activation':['relu', 'elu'],
-       'optimizer': ['Nadam', 'Adam'],
+       'optimizer': ['Adagrad', 'Adam'],
        'losses': ['logcosh'],
        'hidden_layers':[0, 1, 2],
        'batch_size': (20, 50, 5),

diff --git a/docs/Examples_PyTorch_Code.md b/docs/Examples_PyTorch_Code.md
@@ -106,7 +106,7 @@ def breast_cancer(x_train, y_train, x_val, y_val, params):
 
 
 p = {'activation':['relu', 'elu'],
-       'optimizer': ['Nadam', 'Adam'],
+       'optimizer': ['Adagrad', 'Adam'],
        'losses': ['logcosh'],
        'hidden_layers':[0, 1, 2],
        'batch_size': (20, 50, 5),

diff --git a/docs/Examples_Typical.md b/docs/Examples_Typical.md
@@ -55,7 +55,7 @@ return out, model
 ### Parameter Dictionary
 ```python
 p = {'activation':['relu', 'elu'],
-     'optimizer': ['Nadam', 'Adam'],
+     'optimizer': ['Adagrad', 'Adam'],
      'losses': ['logcosh'],
      'hidden_layers':[0, 1, 2],
      'batch_size': (20, 50, 5),

diff --git a/docs/Examples_Typical_Code.md b/docs/Examples_Typical_Code.md
@@ -31,7 +31,7 @@ def iris_model(x_train, y_train, x_val, y_val, params):
 
 # set the parameter space boundaries
 p = {'activation':['relu', 'elu'],
-     'optimizer': ['Nadam', 'Adam'],
+     'optimizer': ['Adagrad', 'Adam'],
      'losses': ['categorical_crossentropy'],
      'epochs': [100, 200],
      'batch_size': [4, 6, 8]}

diff --git a/docs/Hidden_Layers.md b/docs/Hidden_Layers.md
@@ -18,7 +18,7 @@ When hidden layers are used, `dropout`, `shapes`, `hidden_layers`, and `first_ne
 ```python
 
     p = {'activation':['relu', 'elu'],
-         'optimizer': ['Nadam', 'Adam'],
+         'optimizer': ['Adagrad', 'Adam'],
          'losses': ['logcosh'],
          'shapes': ['brick'],          # <<< required
          'first_neuron': [32, 64],     # <<< required

diff --git a/examples/Functional Model Hyperparameter Optimization.ipynb b/examples/Functional Model Hyperparameter Optimization.ipynb
@@ -125,7 +125,7 @@
     "     'epochs': [100],\n",
     "     'dropout': [0],\n",
     "     'kernel_initializer': ['uniform','normal'],\n",
-    "     'optimizer': ['Nadam', 'Adam'],\n",
+    "     'optimizer': ['Adagrad', 'Adam'],\n",
     "     'losses': ['binary_crossentropy'],\n",
     "     'activation':['relu', 'elu'],\n",
     "     'last_activation': ['sigmoid']}"

diff --git a/examples/Hyperparameter Optimization on Keras with Breast Cancer Data.ipynb b/examples/Hyperparameter Optimization on Keras with Breast Cancer Data.ipynb
@@ -2,20 +2,21 @@
  "cells": [
   {
    "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "<img src='https://raw.githubusercontent.com/autonomio/hyperio/master/logo.png' width=250px>"
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "This notebook is a compliment to the *Hyperparameter Optimization on Keras* article. "
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "## Overview\n",
     "\n",
@@ -28,19 +29,20 @@
     "3) Defining the Parameter Space Boundaries \n",
     "\n",
     "4) Running the Experiment"
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "## 1. The Required Inputs and Data"
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "from tensorflow.keras.models import Sequential\n",
     "from tensorflow.keras.layers import Dropout, Dense\n",
@@ -50,33 +52,33 @@
     "import sys\n",
     "sys.path.insert(0, '/Users/mikko/Documents/GitHub/talos')\n",
     "import talos"
-   ],
-   "outputs": [],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# then we load the dataset\n",
     "x, y = talos.templates.datasets.breast_cancer()\n",
     "\n",
     "# and normalize every feature to mean 0, std 1\n",
     "x = talos.utils.rescale_meanzero(x)"
-   ],
-   "outputs": [],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "## 2. Creating the Keras Model"
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# first we have to make sure to input data and params into the function\n",
     "def breast_cancer_model(x_train, y_train, x_val, y_val, params):\n",
@@ -106,20 +108,20 @@
     "                        verbose=0)\n",
     "\n",
     "    return history, model"
-   ],
-   "outputs": [],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "## 3. Defining the Parameter Space Boundary"
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# then we can go ahead and set the parameter space\n",
     "p = {'first_neuron':[9, 10, 11],\n",
@@ -128,24 +130,26 @@
     "     'epochs': [100],\n",
     "     'dropout': [0],\n",
     "     'kernel_initializer': ['uniform','normal'],\n",
-    "     'optimizer': ['Nadam', 'Adam'],\n",
+    "     'optimizer': ['Adagrad', 'Adam'],\n",
     "     'losses': ['binary_crossentropy'],\n",
     "     'activation':['relu', 'elu'],\n",
     "     'last_activation': ['sigmoid']}"
-   ],
-   "outputs": [],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "## 4. Starting the Experiment"
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
    "source": [
     "# and run the experiment\n",
     "t = talos.Scan(x=x,\n",
@@ -155,11 +159,7 @@
     "               experiment_name='breast_cancer',\n",
     "               round_limit=50,\n",
     "               disable_progress_bar=True)"
-   ],
-   "outputs": [],
-   "metadata": {
-    "collapsed": true
-   }
+   ]
   }
  ],
  "metadata": {
@@ -183,4 +183,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}
diff --git a/examples/Hyperparameter Optimization with Keras for the Iris Prediction.ipynb b/examples/Hyperparameter Optimization with Keras for the Iris Prediction.ipynb
@@ -145,7 +145,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from tensorflow.keras.optimizers import Adam, Nadam\n",
+    "from tensorflow.keras.optimizers.legacy import Adam, Adagrad\n",
     "from tensorflow.keras.activations import softmax\n",
     "from tensorflow.keras.losses import categorical_crossentropy, logcosh\n",
     "\n",
@@ -154,7 +154,7 @@
     "     'batch_size': [2, 3, 4],\n",
     "     'epochs': [200],\n",
     "     'dropout': (0, 0.40, 10),\n",
-    "     'optimizer': [Adam, Nadam],\n",
+    "     'optimizer': [Adam, Adagrad],\n",
     "     'loss': ['categorical_crossentropy'],\n",
     "     'last_activation': ['softmax'],\n",
     "     'weight_regulizer': [None]}"